for Early Risk Detection in Projects
ADVISORY ARTICLE
By Devin Partida
New York, USA
A significant part of successful project management involves the early mitigation of identified risks. Then, those overseeing the progress can address problems before they affect budgets, timelines or other aspects. Data analytics tools process vast amounts of data with impressive speed, detecting trends, anomalies or other aspects potentially connected to elevated risks. How can project managers strategically apply them for the best results?
Set Goals for Developing and Using Risk Analysis Applications
Since data analytics tools can handle information much faster than humans, some of the most effective applications involve risk analysis strategies that reduce or eliminate manual or error-prone processes. Consider how long it would take if people manually reviewed the transactions of every credit and debit card holder.
Fortunately, banks and other financial companies use automated data analysis tools that can flag suspicious transactions in near real time. Then, humans can look closer at those most needing their attention.
In one example, a bank used artificial intelligence to reduce trade-related risks. The organization handles approximately 9 million global trading transactions each year. Reviewing them was a time-intensive and highly manual process before it began using AI. The bank’s selected analytics platform also provides enhanced risk insights, shortening the response times for investigating issues.
Whether a project manager’s potential use case relies on AI or another data analysis technology, they should clearly define which information they want to examine, the average volume in a given time frame and which risks they hope to detect. Determining those specifics will allow them to develop and implement targeted solutions on schedule and within a stated budget.
Create Plans for Dealing with Identified Risks
Although data analytics can flag risks for project managers, these professionals still need to consider how they will handle those matters when they arise. One best practice comes from the health care industry. Many patients get annual medical screening tests, especially if their family histories feature certain cancers or their physicians have other concerns.
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How to cite this article: Partida, D. (2024). Leveraging Data Analytics for Early Risk Detection in Projects, PM World Journal, Vol. XIII, Issue X, October/November. Available online at https://pmworldlibrary.net/wp-content/uploads/2024/11/pmwj146-OctNov2024-Partida-Leveraging-Data-Analytics-for-Early-Risk-Detection-in-Projects-1.pdf
About the Author
Devin Partida
New York, USA
Devin Partida is an editor and writer currently residing in Upstate New York. She is the Editor-in-Chief of ReHack.com and is especially interested in writing about business operations and BizTech topics. Devin’s work has been featured on Entrepreneur, Forbes and Nasdaq.com. She can be contacted at devin@rehack.com
